A comparative evaluation of mobile medical APPS (MMAS) for reading and interpreting malaria rapid diagnostic tests

Abstract

Background The World Health Organization recommends confirmatory diagnosis by microscopy or malaria rapid diagnostic test (RDT) in patients with suspected malaria. In recent years, mobile medical applications (MMAs), which can interpret RDT test results have entered the market. To evaluate the performance of commercially available MMAs, an evaluation was conducted by comparing RDT results read by MMAs to RDT results read by the human eye. Methods Five different MMAs were evaluated on six different RDT products using cultured Plasmodium falciparum blood samples at five dilutions ranging from 20 to 1000 parasites (p)/microlitre (µl) and malaria negative blood samples. The RDTs were performed in a controlled, laboratory setting by a trained operator who visually read the RDT results. A second trained operator then used the MMAs to read the RDT results. Sensitivity (Sn) and specificity (Sp) for the RDTs were calculated in a Bayesian framework using mixed models. Results The RDT Sn of the P. falciparum (Pf) test line, when read by the trained human eye was significantly higher compared to when read by MMAs (74% vs. average 47%) at samples of 20 p/µl. In higher density samples, the Sn was comparable to the human eye (97%) for three MMAs. The RDT Sn of test lines that detect all Plasmodium species (Pan line), when read by the trained human eye was significantly higher compared to when read by MMAs (79% vs. average 56%) across all densities. The RDT Sp, when read by the human eye or MMAs was 99% for both the Pf and Pan test lines across all densities. Conclusions The study results show that in a laboratory setting, most MMAs produced similar results interpreting the Pf test line of RDTs at parasite densities typically found in patients that experience malaria symptoms (> 100 p/µl) compared to the human eye. At low parasite densities for the Pf line and across all parasite densities for the Pan line, MMAs were less accurate than the human eye. Future efforts should focus on improving the band/line detection at lower band intensities and evaluating additional MMA functionalities like the ability to identify and classify RDT errors or anomalies.

Use of a health worker-targeted smartphone app to support quality malaria RDT implementation in Busia County, Kenya: A feasibility and acceptability study

“…These limitations include its low battery life, low functionality in high-dirt environments, and difficulty to use among unskilled health workers [ 21 , 22 ]. Similar results were found in a comparative evaluation of another mHealth tool used for reading and interpreting mRDTS [ 23 ]. Other POCT reader devices include handheld lateral flow immunoassays (LFIA) [ 24 , 25 ] and the mHAT RDT reader application (app) [ 26 ], although the functionality of these devices in the field is still limited and being explored [ 27 ].…”

Analysis of Factors Affecting Neutralizing Antibody Production after COVID-19 Vaccination Using Newly Developed Rapid Point-of-Care Test

“…As shown in Table S3 , the newly developed POCT showed excellent performance comparable to that of the ELISA, although the sensitivity was slightly lower. In the interpretation of POCT, visual reading can make interpretation errors, so research is focused on making accurate and improved measurements through interpretation devices [ 28 , 29 ]. When the signal intensity of neutralizing antibody was measured using an application, the T/R ratio cutoff increased in the sensitivity of the POCT.…”

Performance Evaluation of the BZ COVID-19 Neutralizing Antibody Test for the Culture-Free and Rapid Detection of SARS-CoV-2 Neutralizing Antibodies

“…Visual interpretation of RDTs is subjective with variable results depending on the interpreter. Analyzing RDTs with SIA has been reported to provide improved and reliable results [ 18 , 19 , 20 ]. In this study, when the signal intensity of BZ-nAb was measured using the SIA, the T/C ratio cutoff led to an increase in the sensitivity of the BZ-nAb from 92.5% to 95.0%, impacting its performance, although at the expense of its specificity.…”

“…In addition to visual interpretation, the signal intensity of each line (both test and control) was analyzed using a smartphone-based image analysis application (SIA). With the development of mobile medical applications for automated interpretation of RDT results, analyzing RDTs with these applications has been reported to provide improved and reliable results [ 18 , 19 , 20 ]. A pilot study of SIA evaluation using different immunochromatographic assay and results showed acceptable performance (100% sensitivity and 97.8% specificity) when compared to visual interpretation results (data not shown).…”